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CHAPTER 22 Does Climate Change Make Industrialization An Obsolete Development Strategy for Cities in the South? Le-Yin Zhang* Summary This paper attempts to explore the implications of climate change for economic development strategies in cities in the South. In particular, it examines whether climate change makes industrialization an obsolete development strategy for these cities. It starts by examining the effects of climate change and the challenges posed for the cities concerned, followed by a discussion of the role of industrialization in economic development and climate change. It then investigates how these issues affect Southern cities by considering the experiences of Shanghai, Mumbai and Mexico City. In conclusion, the paper hypothesizes that climate change will make industrialization a more, not less, important development strategy, even for those cities that are currently affected by pre-mature deindustrialization. *Corresponding author: [email protected] 564 Q CHAPTER 22 Q 565 1. INTRODUCTION In a world of rapid urbanization and global integration, climate change represents only one of the many challenges that cities in the South have to grapple with in the coming decades. It is nevertheless a fundamentally important challenge for these cities because failing it will not only diminish their own long-term prospects, but also let the world seriously down. This is for several reasons. First, developing countries already produce more than half of the total global emissions, and this share is rising fast. Non-OECD emissions of carbon dioxide exceeded OECD emissions by 7 percent in 2005, and are projected to exceed those from the OECD countries by 72 percent in 2030 (International Energy Agency 2008). Therefore, although developing countries are under no formal obligation at the present to mitigate, this is bound to change. Second, any prospective changes in terms of mitigation obligation will primarily affect cities in the South, as they embody a majority of the economic activities there.1 Third, concerns about climate change have the potential to bring forward a new energy system and, associated with it, a new international trading environment. If some of the legislative changes (e.g. cap-and-trade scheme in USA) currently proposed are to become reality, this could substantially alter the comparative advantage of developing countries, with great impact on cities in their role as bridgeheads of international trade. Therefore climate change can affect and be affected by economic development pathways in a fundamental way. This is why climate change has to be mainstreamed through economic development strategies (Zhang 2008). Accordingly, this paper attempts to explore the implications of climate change (and its impact) for economic development strategies in cities of developing countries. In particular, it examines whether climate change makes industrialization a less viable development strategy for these cities, since industrial activities are a major source of emissions in the South (see Figure 2). The paper starts by examining the effects of climate change and the challenges that it poses for developing cities, especially in terms of industrialization. This is followed by a discussion of the role of industrialization in economic development, and the relationship between industrialization and climate change issues, highlighting tensions as well as synergy between the two. The paper then examines how these issues are affecting developing cities by considering the experiences of Shanghai, Mumbai and Mexico City. It concludes that industrialization still represents a viable and, to some extent, indispensable development strategy for these cities in the context of climate change, even for those that are affected by pre-mature deindustrialization. 1Urban-based economic activities account for up to 55 per cent of gross national product (GNP) in low-income countries, 73 per cent in middle-income countries and 85 per cent in high income countries (UN-HABITAT 2006). 566 Q CITIES AND CLIMATE CHANGE 2. CLIMATE CHANGE AND DEVELOPING COUNTRIES 2.1 The Challenge of Climate Change Climate change mitigation poses a potentially serious challenge for developing countries. As Table 1 shows, although tCO2-eq emissions per capita in these countries were only one-fourth of those in Annex I countries by 2004, they had already exceeded the so-called ‘emissions budget’ by a factor of 4 and were responsible for more than half of the total emissions.2 On the other hand, GHG emissions per unit of GDP were 50% higher in non-Annex-I countries, which means that there is significant scope for mitigation in developing countries. Moreover, even if there is no immediate obligation to mitigate, there is growing economic incentive to do so in the context of an emerging global carbon market and the Clean Development Mechanism under the Kyoto Protocol (Zhang 2008). However, since their population and economic growths are generally faster than in developed countries, faster reductions in emissions intensity will be needed in order to offset these growths so as to achieve de-carbonization. As the Kaya Identity suggests (see Equation 1), this can be achieved by either reducing energy intensity (i.e. energy/GDP), or reducing the carbon intensity of energy (i.e. CO2 emissions /energy). Key strategies include improving energy use efficiency, industrial restructuring (i.e. reducing the weight of energy-intensive economic activities) and energy switch (i.e. reducing the weight of emission-intensive fuels). Kaya Identity (Nakicenovic et al. 2000 ): Equation 1: CO2 emissions = Population X (GDP/Population) X (energy/GDP) X (CO2 emissions/energy) Equation 2: CO2 emissions = Population X (GDP/Population) X (CO2/GDP) TABLE 1 Distribution of global GHG emissions (2004) Grouping tCO2 eq/ cap KgCO2 eq/ US$GDPppp(2000) Share in Global Totals (%) Population GDP Emissions Annex I countries 16.1 0.683 19.7 56.6 46.4 Non-Annex I countries 4.2 1.055 80.3 43.4 53.6 Source: Rogner et al. 2007, p.106, Figure 1 .4a and Figure 1 .4b. a: all Kyoto gases including those from land-use. 2The Third Assessment Report (Banuri et al 2001, p. 89) notes that stabilization of CO2 in the atmosphere at 450 ppm would require limiting global carbon emissions to about 3 billion tons by 2100, equivalent to 0.3 tonne of carbon per capita. The last is equivalent to 1.1 metric tons of carbon dioxide. CHAPTER 22 Q 567 On the other hand, developing countries face an even greater challenge in adaptation. This is principally concerned with reducing vulnerability and developing adaptive capacity (Burton, Diringer, and Smith 2006), although by definition adaptation should also aim to exploit the beneficial opportunities. When defined as “the likelihood of injury, death, loss, disruption of livelihoods or other harm” (Eriksen and O’Brien 2007, p.338), vulnerability inevitably affects populations whose livelihood or wellbeing is already undermined by high incidence of poverty. However, developing countries are more at risk also because of their geography, greater reliance on agriculture and lower adaptive capacity (Burton, Diringer, and Smith J. 2006; McCarthy et al. 2001; World Bank 2008). This places premium on non-agricultural productive activities and factors that strengthen their adaptive capacity, which include economic resources, technology, information and skills, infrastructure, institutions and equity (Smit et al. 2001)—in other words, the products of industrialization. Thus developing countries need to take action in both mitigation and adaptation, aiming at reduction of emissions, reduction of poverty and vulnerability, and the strengthening of adaptive capacity. What does this mean for their economic development strategies? 2.2 The Implication For Economic Development in the South The Special Report on Emissions Scenarios (SRES) (Nakicenovic et al. 2000) is relevant here. Guided by the Kaya Identity and building upon a common set of driving forces, including global population growth, economic development, technological diffusion, energy systems and land use, and assuming that no specific climate policies are implemented, the SRES outlines a set of four alternative scenario ‘families’ comprising 40 SRES scenarios. These scenarios indicate a wide range of CO2 emission possibilities, ranging from less than 10 GtCO2 to almost 35 GtCO2 by 2100 (see Figure 1). The corresponding CO2 concentration and global mean temperature increase (from 1990 to 2100) varies respectively from 500 to 1000 ppm and from 1.3oC to 5.8 oC, with the B1 scenario offering the lowest emissions. The drivers of the six illustrative scenarios are summarized in Table 2. Figure 1 and Table 2 demonstrate a striking range of future possibilities. First, with everything else being equal, the A1 scenario, characterized by fast economic growth and population growth, could either lead to extremely high emissions or intermediate to low emissions, depending on the nature of the energy systems. Second, combining a service-based economy with cleaner energy produces B1, a scenario of very low emissions (lower than the level of 1990). Third, a combination of intermediate growth rates for the economy and population, and lower degree of global convergence would result in B2, characterized by relatively low emissions level, which is nevertheless higher than the level of 1990. Finally, 568 Q CITIES AND CLIMATE CHANGE the worst scenario would be A2, characterized by slow economic growth, fast population increase, less global convergence and very high emissions level. These contrasting scenarios point to one conclusion: the rate of economic growth is not the decisive factor for mitigation. Much will depend on the kind of energy systems developed and the economic structure. FIGURE 1 Emissions Scenarios Source: Nakicenovic et al. 2000, Figure TS-8. Each colored band shows the projected emissions of the six illustrative scenarios. However, it would be mistaken to conclude from the SRES that developing economies should bypass industrialization or pursue de-industrialization at all costs. This is true despite the fact that industry is a major source of emissions. Industry accounts for 19.4% of global GHG emissions in 2004, and including energy supply increases industry’s share to more than 40% of total emissions (IPCC 2007). Moreover, the share of industry related emissions is even higher in developing countries. According to Price et al (2006), the SRES divided all emissions under four headings, namely industry, building, transport, and agriculture. Analysis of the detailed non-agricultural emissions data shows that the share of industry in non-agricultural emissions declined from 55.4% in 1971 to 49.8% in 2000 in these countries. However it is projected to rise to 51% in 2020 under scenario A1 and 51.9% under scenario B2 (see Table 3 and Figure 2). CHAPTER 22 Q 569 TABLE 2 Emissions Scenarios and Drivers Key Drivers Of Emissions Illustrative Emissions Scenarios Economic Growth A1 Fast A2 slow B1 fast B2 Intermediate Economic Structure Population Growth Global Convergence Peaks in mid-21st century, then declines Fast Continuously increasing Towards a service and information economy Energy Systems A1FI Fossil energy intensive A1T Non-fossil energy sources A1B Balanced energy sources slow Same as A1 Cleaner technology Slower, more diverse than B1 and A1 Similar to A2, but at lower rate Source: Own elaboration on the basis of Nakicenovic et al. 2000, p. 22 TABLE 3 Historical and Projected Non-Agricultural GHG Emissions by Developing Countries Year CO2 Emissions (MtC) Industry’s Share of Total (%) Developing Countries’ Share in Total NonAgricultural Emissions Industry Building Transport Total 1971 288 127 105 520 55.38 14.3 2000 1016 593 430 2039 49.83 34.5 2020 (A1) 3147 1361 1668 6176 50.96 53.2 2020 (B2) 2001 833 1019 3853 51.93 44.0 Source: Price et al. 2006. Own calculation. 2020 (A1) and 2020 (B2) represent respectively projections for SRES A1 and SRES B2 scenarios. Developing countries here include: centrally planned Asia, other Asia, Latin America, Sub Saharan Africa, and Middle East/North Africa. 570 Q CITIES AND CLIMATE CHANGE Interestingly, the data (see Table 3) show that high industrial emissions in developing countries does not mean high share of global non-agricultural emissions by these countries. Indeed, the data show that, under scenario B2, although industry’s share is as high as 52% in total non-agricultural emissions in 2020, these countries’ share in total emissions could be as low as 44%. This is prime facia evidence that increased industrial emissions, a likely outcome of industrialization, do not have to mean high emissions for developing countries. In other words, there is no reason to think that industrialization will become less viable because of the need for CO2 mitigation. FIGURE 2 Importance of Industry-Related Emissions Composition of Carbon Emissions in Non-agricultural Sectors 100 80 60 40 20 0 1971 2000 2020(A1) 2020(B2) Year Industry Building Transport Source: Table 3. Having said this, there are other important reasons why industrialization cannot be abandoned as a development strategy. We explore this below. CHAPTER 22 Q 571 3. INDUSTRIALIZATION AS AN ECONOMIC DEVELOPMENT STRATEGY FOR SOUTHERN CITIES 3.1 Why Industrialization? According to Martinussen (1997), economic development refers to the process whereby the real per capita income of a country increases over a long period of time while simultaneously poverty is reduced and the inequality in society is generally diminished, or at least not increased. It is characterised by the structural transformation of the economy, or systematic changes in the allocation of factors of production and in improved techniques of production (Meier 1995:7). Industrialization, changes in demand and trade patterns, and urbanization are key aspects of such changes (Kuznets 1966; Syrquin 1988). A principal objective of any economic development strategy is to enhance the prospects for sustained economic growth, poverty reduction and structural transformation. Industrialization, a process in which the share of industry (especially manufacturing) in both national income and employment increases in a country (Dasgupta and Singh 2006: 18), has traditionally played an important role in the economic development of almost every country (Chenery, Robinson and Syrquin 1986). Indeed, it distinguishes three stages in the process of their economic development: 1) primary production, when the production of primary goodstypically agricultural products- dominates the economy; 2) industrialization; and 3) developed economy, characterized by de-industrialization, the process when manufacturing’s share in employment and then in GDP declines while the weight of services increases. During the course of industrialization, per capita income was found to rise from $400 to $2100 in 1970 dollars (equivalent to a change from $1,734 to $9,127 in 2007 dollars) in a selection of 38 significant economies.3 The process of industrialization is the most dynamic phase in the course of development, characterized by fast economic growth and technological progress, shift of resources from less to more productive activities and the building-up of the so-called ‘social overhead’ (i.e. basic infrastructure) (Young 1928; Kaldor 1966; Kaldor 1978). Many of the benefits of industrialization derive from the economies of scale uniquely associated with the manufacturing industry. The Kaldor’s growth laws state: t There exists a strong positive correlation between the growth of manufacturing output and the growth of GDP; t There exists a strong positive correlation between the growth of manufacturing output and the growth of productivity in manufacturing t There exists a strong positive relationship between the growth of manufacturing output and the growth of productivity outside of manufacturing (Thirlwall 2003) 3The 2007 amounts are calculated by using the GDP deflator provided on http://www.measuringworth.com/ uscompare/ . 572 Q CITIES AND CLIMATE CHANGE Moreover, industrialization is also an effective means for poverty reduction (Fukunishi et al. 2006). Cross-country experiences have shown that, to lift a large number of people out of poverty, one of the essential ingredients is to provide the poor with the opportunities to use their most abundant asset, namely labour (World Bank 1990, p. 51). In this regard, export-oriented industrialization is particularly effective, as it enables the exploitation of a market much larger than the domestic market, and creates jobs for a significant number of semi-skilled workers. It also has positive impact on distribution. Industrialization could also fundamentally strengthen adaptive capacity by diversifying the economy and promote socio-economic features that strengthen adaptive capacity. One of the most interesting works in this area is a study by Roberts & Parks (2007). From analyzing a universe of more than 4,000 climaterelated disasters across the world over the past two decades, these authors found that, when other factors are held constant, national poverty explained virtually none of the trends in deaths and homelessness. Instead, they found that people living in more urbanized nations were less likely to be killed, made homeless, or affected by climate related disasters than people living in more rural nations. Furthermore, a narrow export base explained about 1/3 of homelessness, from 1/7 to 1/3 of deaths, and about 40% of national patterns in who were affected by climate-related disasters. Since industrialization effectively increases the diversity of exports and strengthens urbanization, it can in turn reduce some common causes of vulnerability. The above discussion demonstrates that industrialization remains a viable and important development strategy in the context of climate change. Despite this connection, some metropolitan cities in developing countries are already experiencing de-industrialization. 3.2 De-Industrialization De-industrialization, evidenced by the fall in the share of manufacturing employment or an absolute fall in such employment (Dasgupta and Singh 2006), has both demand-side and supply-side causes (Rowthorn and Ramaswamy 1999). The experiences of London and Glasgow (Graham & Spence 1995; Lever 1991) demonstrate that two other factors are influential in the de-industrialization of metropolitan economies. First, competition for increasingly expensive real-estate could drive manufacturing activities out of the urban centre. Second, mis-guided policy attempts to de-congest established urban areas have similar effects. However, de-industrialization e-industrialization has predictable and predominantly negative consequences for low-income economies. It generally slows down overall productivity rise (i.e. economic growth and income rises) and causes unemployment and dereliction. It affects the semi-skilled labours most strongly, but also has wider CHAPTER 22 Q 573 repercussions around the economy. The crux of the matter is that such negative effects can not be compensated in low-income economies by the growth of other productive economic activities (e.g. knowledge-based and high-value added services) due to the lack of requisite skills and other kinds of capital. Unfortunately, however, many developing countries are apparently undergoing de-industrialization while still at a low level of development (with a per capita GDP of around US$3000). Dasgupta and Singh (2006) describes this as “pre-mature de-industrialization”. They identified two paradigms of de-industrialization since the 1980s: 1) the Indian type, where manufacturing employment is not expanding in the formal sector, but is growing within a large informal sector, and there is nevertheless expansion of manufacturing products. 2) The Latin American and African type, where contraction in manufacturing stops the economy from achieving its full potential of growth, employment and resource utilization. In the context of climate change, since manufacturing produces the material inputs for infrastructure (and for construction), pre-mature de-industrialization would reduce these countries’ ability to develop infrastructure and more generally adaptive capacity. 3.3 The Way Out: Industrialization Coupled with De-Carbonisation The above analysis suggests that there is synergy as well as tension between industrialization and climate change policy goals. While industrialization accelerates productivity and technological changes, reduce poverty and vulnerability, and facilitates the development of adaptive capacity, industry presently also produces a large amount of emissions. So what is the way out? The Kaya Identity indicates that in order to retain the benefits of industrialization, the only way out is de-carbonization (i.e. the reduction of emissions intensity). This means that industrialization has to be combined with de-carbonisation to remain a viable economic development strategy. Difficult as this may sound, de-carbonizing industrialization is probably more feasible than it appears. An important insight in the clean industrial production literature is that “new paths are always pioneered outside the dominant regions.” (Robins and Kumar 1999, p.78). Such precedents include the American invention of mass production of automobiles and the Japanese pioneering of lean manufacturing. On the other hand, existing energy research suggests that emissions reduction depends on technological progress, retirement of inefficient technologies, changes in the structure of energy systems and patterns of energy services (Nakicenovic et al. 2006), all of which are enhanced by industrialization. This explains why developing countries are projected to continue to reduce energy intensity more quickly than developed countries because of the greater scope for technological advancement and improvement in energy use (IEA 2007). 574 Q CITIES AND CLIMATE CHANGE The decarbonization of industry, while still in its infancy, is indeed already happening. For example, a study by Chandler et al. (2002) of mitigation experiences in six large developing countries (Brazil, China, India, Mexico, South Africa and Turkey) shows that efforts undertaken by these countries, often unrelated to climate policies, have reduced their emissions growth over the past three decades (1970s-1990s) by approximately 300 million tons a year. In particular, energy intensity started to fall from 1995 in India and declined by an average of 4% per annum during 1977-1997 in China. More importantly, these countries have significant scope for further mitigation: experts estimated that India could reduce projected emissions over the next 30 years by nearly one-quarter for less than $25 per ton of carbon equivalent. Another encouraging sign is that, according to a recent HSBC report (Robins, Clover and Singh 2009), it is China and South Korea, not USA, that lead the green investment league table in their fiscal stimulus packages in response to the on-going global financial turmoil started in 2007-08. The Chinese investment is more than twice as large as the USA’s. In conclusion, we have reasons to hypothesize that climate change does not make industrialization an obsolete development strategy for cities in the South. On the contrary, it may even make it more important than ever before. This is because, in comparison with de-industrialization, decarbonising industrialization has much greater potential to reduce emissions intensity, to reduce poverty and vulnerability, and to strengthen adaptive capacity in these cities. This is summarized in Table 4. TABLE 4 Summary of Strategies and Their Potentials Strategies and Outcomes Potential to Reduce Emissions Intensity Reduce Poverty and Vulnerability Strengthen Adaptive Capacity De-industrialization M L L Decarbonising industrialization H H H Source: Own elaboration. Note: H = High; M = Medium; L= Low. CHAPTER 22 4. Q 575 EVIDENCE FROM THREE CITIES In this section, an attempt is made to examine how the issues raised above are affecting Southern cities with case studies of Shanghai, Mumbai and Mexico City. To start with, each of these three cities is the most important economic powerhouse of their home economies, which are of course at different levels of development. As Table 5 shows, both GNI per capita and emissions per capita is highest in Mexico and lowest in India. However, emissions per capita in China are very close to Mexico’s, although its GNI per capita is less than one-fourth of Mexico’s. This is explained by the differences in their energy systems and economic structures: as Table 6 shows, industry is much more important in China’s economy than Mexico’s. Furthermore, Table 5 shows that economic growth is much faster in China than in Mexico or India. TABLE 5 Country Profiles for China, India and Mexico GDP Annual Growth (%) Emissions (metric tons per capita) (2004) GNI per Capita (Atlas method, US$) (2004) 1990-2000 2000-05 India 1.24 630 4.2 4.7 China 3.86 1500 10.6 9.6 Mexico 4.29 6930 3.1 1.9 Indicator Source: World Development Indicators 2007. Interestingly, measured by absolute fall in manufacturing employment, China started to de-industrialize the earliest in 1992 (partly as a correction of its over-industrialization before the onset of its economic reform), followed by India in 1997 and Mexico in 2000 (Table 6). In terms of industrial value-added as percentage of GDP (a less reliable indicator for industrialization/de-industrialization due to short-term price changes), China and India appear to have followed a trend of industrialization/re-industrialization since 2000, whereas the trend in Mexico is less clear. 576 Q CITIES AND CLIMATE CHANGE TABLE 6 De-industrialization in China, India and Mexico Manu. Employment (1,000) 1990 Manufacturing Employment (1,000) China India 53040 6118 1991 1992 Mexico 28 28 46 26 28 48 27 26 49 30 36 3838 6767 1997 7068 32400 6119 5749 5178 2005 2007 India 42 55417 1995 2003 China 3628 1993 2000 Mexico Industry Value-Added as % of GDP 5449 Source: International Labour Organisation (1998 -2009); World Development Indicators online database. At the city level, all three cities have de-industrialized, although to different extents and with varying levels of importance for manufacturing (Table 7). Of the three cities, Shanghai is the most industrialized with industrial jobs accounting for 32% of total employment in 2006. Mexico City was the earliest to begin de-industrializing, beginning probably even before 1970, followed by Mumbai (from early 1980s) and finally Shanghai in 1990. Interestingly, these cities have done so for quite different reasons, in addition to normal demand and supply factors. In Mumbai, this was largely due to the effects of the 1981 textile workers strike and the land ceiling policy (Pacione 2006). In the case of Mexico City, the rise of manufacturing along the USA-Mexico border and de-concentration policy played a role (Grajales forthcoming). Finally in the case of Shanghai, the government’s prioritization policies as well as surging domestic demand for services are responsible (Zhang 2003). CHAPTER 22 Q 577 TABLE 7 De-industrialization Trends in Mumbai, Shanghai and Mexico City Greater Mumbai (Manufacturing employment as % of total employment) Shanghai (Industrial employment as % of total employment) 1960 21.26 1970 23.80 1980 1985 42.90 35.97 23.78 53.88 1990 28.47 1995 18.61 49.96 1998 2000 2006 23.78 44.30 1988 1993 Mexico City Metropolitan Area (Manufacturing share in GDP) 19.21 17.84 39.72 32.13 Sources: Mumbai Metropolitan Regional Development Authority (2001); Grajales (forthcoming) and Shanghai Statistical Yearbook (various years). Industrial employment for Shanghai covers manufacturing and utilities. Although the lack of comparable data precludes any attempt to quantify the effect of de-industrialization, it is evident that the three cities perform differently in economic terms. Grajales (forthcoming) notes that from 1980 to 1998, Mexico City Metropolitan Area progressively slid down the national labour productivity league table for metropolitan areas from the 8th place to 19th place. Mumbai’s annualized GDP growth rate registered 8.5% from 2001/2 to 2006/7, which is only slightly above the national growth rate of 8% for the same period (The Economic Times, 20 Jan. 2008). Its economic structure, characterized by a small manufacturing sector and a large group of low value-added ‘other services’, is a likely contributor to this outcome (Figure 3: De-Industrialization in Mumbai). In comparison, Shanghai’s GDP grew by 12.5% per annum between 1992 and 2007, compared with 9.4% per annum for the national average (1992-2006). It would seem that economic structure matters here too. 578 Q CITIES AND CLIMATE CHANGE FIGURE 3 De-Industrialization in Mumbai Industrial Transformation of Greater Mumbai, 1980 to 1998 Source: Mumbai Metropolitan Regional Development Authority 2001. There is also evidence that industry is not where the greatest mitigation challenge lies. This is clearly illustrated by the experience of Shanghai. While energy consumption has declined significantly in industry, it has risen rapidly in the rest of the economy and in the household sector (by 14.64% between 2005 and 2006 in the latter) (Table 8 and Table 9). Furthermore, while energy intensity is higher in the secondary sector (especially in industry) than elsewhere, it is falling fast, by 6.18% from 2005 to 2006 alone. By contrast, energy intensity is increasing (although only slowly) in the tertiary sector. These mean that the greatest mitigation challenge will be to contain the growth of energy consumption outside industry even in Shanghai, the most industrialized city of the three. TABLE 8 Allocation of electricity consumption in Shanghai in 1990, 2000 and 2007 Year Industry (%) Agriculture (%) Households (%) The Rest (%) 1990 83.5 2.7 5.5 8.4 2000 70.3 1.6 9.5 18.6 2007 65.8 0.5 12.2 21.5 Source: Shanghai Statistical Yearbook 2008. CHAPTER 22 Q 579 TABLE 9 Unit energy consumption of different economic activities, Shanghai, 2006 Indicators Energy /GDP Unit Amount Change Over 2005 (%) TSC/Yuan 8370 -3.71 - Primary sector TSC/Yuan 9840 -7.79 - Secondary TSC/Yuan 11120 -6.08 TSC/Yuan 11600 -6.18 - Tertiary TSC/Yuan 4950 0.13 Household energy consumption 1,000 TSC 7535.1 14.64 Energy/value added Of which: industry Source: Shanghai Statistical Bureau 2006. TSC stands for tons of standard coal. 5. CONCLUSION This paper has attempted to examine the implication of climate change for economic development strategies for Southern cities, focusing on the question whether climate change makes industrialization an obsolete strategy. Through the lens of Kaya Identity, industrial history, and theories of industrialization and de-industrialization, and considering the development experiences in Shanghai, Mumbai and Mexico City, it demonstrates that this is not so. Indeed, it advances the hypothesis that climate change will make industrialization a more important strategy than ever before. The implications are several-fold. First, addressing climate change does not call for the abandonment of industrialization, or pre-mature de-industrialization. Second, however, industrialization cannot carry on with its present mode of development—industries must be de-carbonized for the sake of local and national long-term prosperity as well as global sustainability. Finally, if the preliminary trend of decreasing energy intensity in Shanghai is any guide, then this can be achieved. Further research is needed, however, to formulate the practical ways forward. 580 Q CITIES AND CLIMATE CHANGE References Banuri, T., J. Weyant, G. Akuma, A. Najam, L. Pinguelli Rosa, S. Rayner, W. Sachs, R. Sharma, and G. Yohe. 2001. Setting the stage: Climate change and sustainable development. Cambridge: Cambridge University Press. Burton, I., E. Diringer, and J. Smith. 2006. Adaptation to Climate Change: International Policy Options. Arlington, USA: Pew Center on Global Climate Change. Chandler, W., D. Schaeffer, D. Zhou, P. Shukla, F. Tudela, O. Davidson, and S. AlpanAtamer. 2002. Climate Change mitigation in developing countries: Brazil, China, India, Mexico, South Africa, and Turkey. Washington, D.C.: Pew Center on Global Climate Change. Chenery, H., S. Robinson, and M. Syrquin. 1986. Industrialization and Growth: A Comparative Study. 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